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0 2 4 6 8 C ongruent Incongruent ErrorR ate (% ) 0 2 4 6 8 C ongruent Incongruent ErrorR ate (% ) 10 20 30 40 2 5 10 15 20 25 30 Frequency (H z) R elative pow er(dB ) - + Stim Resp CRN ERN Pe - + 6Hz Theta Alpha 2 µV Error Correct -100 0 100 200 300 400 500 Time (ms) -100 0 100 200 300 400 500 Time (ms) SUMMARY METHODS RESULTS 3. Ending-trial assessment: RT and CRN were modulated by the preceding context Participants •Right-handed, healthy volunteers •Behavioral task: n=24 (12 males), mean age=24.6, range= 18-35 •EEG + behavioral task: n=24 (12 males), mean age=23.7, range=18-31 Task •Stroop color-identification task requiring button press responses. •2 x 2 x 4(3) repeated measures design with factors of preceding-trial type (congruent vs. incongruent), ending-trial type (Congruent vs. Incongruent), and number of preceding trials (contextual manipulation, cm: 1, 3, 5, [7]). Each cell in the design is referred to as a “mini-block”. • Example of a single “mini-block”: EEG Data Collection •Continuous 128 channel data, sampling rate: 1000Hz, 634.22/CCC15 Department of Psychology 1 , Department of Neurosciences 2 , Department of Computer Science 3 , University of New Mexico, Albuquerque, NM Limited Modulation of the Stroop Interference Effect by up to 3 Preceding Trials M.T. Sutherland 1 and A.C. Tang 1,2,3 REFERENCES ACKNOWLEDGEMENTS 1.CRN and ERN were present in the same frontal-midline component that captured ACC activity. INTRODUCTION Frontal-midline EEG activity in the form of negative deflections in event-related brain potentials (e.g., the error-related negativity, ERN), has been considered to reflect aspects of anterior cingulate cortex (ACC) activity related to performance monitoring [1-6]. Bartholow et al. [5] have shown that the correct-related negativity (CRN, [7]) is sensitive to strategic expectations about an upcoming trial. Using a design where the probability of incongruent (I) or congruent (C) trials was manipulated over large blocks (e.g., C-80%: I-20%), CRN amplitude increased when the less probable trial type was encountered for both I and C trials. CRN modulation for C trials is unexpected according to conflict monitoring [3] because C trials are unlikely to induce response-conflict regardless of context. Bartholow et al. suggested a broadening of the conflict monitoring hypothesis to include other forms of conflict in addition to that at the response level. In the present study a different contextual manipulation was employed to further assess CRN modulation. Previously, the compatibility level (I vs. C) of the preceding trial has been shown to affect reaction times (RTs) and ACC activity on a current trial []. However, the number of preceding trials has not been considered as an important source of variance for current-trial RT. 1. Ridderinkhof K.R., Ullsperger M., Crone E.A., Nieuwenhuiss S. (2004). The role of the medial frontal cortex in cognitive control. Science, 306:443-447. 2. Ullsperger M., von Cramon D.Y. (2004). Neuroimaging of performance monitoring: Error detection and beyond. Cortex, 40:593-604. 3. Botvinick M.M., Braver T.S., Barch D.M., Carter C.S., Cohen J.D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108:624-652. 4. Luu P., Flaisch T., Tucker D.M. (2000). Medial frontal cortex in action monitoring. J. Neurosci., 20:464-469. 5. Bartholow B.D., Pearson M.A., Dickter C.L., Sher K.J., Fabiani M., Gratton G. (2005). Strategic control and medial frontal negativity: beyond errors and response conflict. Psychophysiology. 42:33-42. 6. Taylor S.F., Stern E.R., Gehring W.J. (2007). Neural systems for error monitoring: recent findings and theoretical perspectives. Neuroscientist, 13:160-172. 7. Vidal F., Hasbroucq T., Grapperon J., Bonnet M. (2000). Is the 'error negativity' specific to errors? Biol Psychol, 51:109-128. 8. Botvinick M., Nystrom L.E., Fissell K., Carter C.S., Cohen J.D. (1999). Conflict monitoring versus selection-for-action in anterior cingulate cortex. Nature, 402:179-181. 9. Egner T., Hirsch J. (2005). The neural correlates and functional integration of cognitive control in a Stroop task. NeuroImage, 24:539-547. 10. Gratton G., Coles M.G., Donchin E. (1992) .Optimizing the use of information: strategic control of activation of responses. J Exp Psychol Gen, 121:480-506. 11. Kerns J.G., Cohen J.D., MacDonald A.W., 3rd, Cho R.Y., Stenger V.A., Carter C.S. (2004). Anterior cingulate conflict monitoring and adjustments in control. Science, 303:1023-1026. 12. Belouchrani A., Abed-Meraim K., Cardoso J-F, Moulines E. (1997). A blind source separation technique using second-order statistics. IEEE Trans on Signal Proc, 45:434- 444. 13. Tang A.C., Sutherland M.T., McKinney C.J. (2005). Validation of SOBI components from high density EEG. NeuoImage, 25:539-553. This work was funded by a grant to ACT from the Sandia National Labs (#75111). We thank Amy Korzekwa, Masato Nakazawa, and Zhen Yang for assistance during data collection. 1. The SOBI recovered frontal-midline components likely capture aspects of ACC function. 2. The CRN and ERN may share a similar neural generator since both of these ERP deflections were captured in a single component. 3. The reduction of the Stroop interference effect (I-C) following a preceding i trial, in comparison to following a c trial, was diminished in the current study when only one preceding trial was delivered before the ending-trial of interest (CM-1). 4. The CRN was modulated by the contextual manipulations in the present study. (we need to say what this means to existing theory) 2. Preceding-trial assessment: RT and CRN amplitude differed across preceding trial numbers 4. Modulation of RT was unlikely to be explained as a speed-accuracy tradeoff: Error rates -2 -1.5 -1 -0.5 0 1 2 3 4 5 CRN am plitude (µV) 3rd 4th 1st 2nd 5th Inc. Con. Preceding trial number Incongruent Congruent 2 µV 500 600 700 800 900 1 2 3 4 5 R T (m s) 400 500 600 700 800 1 2 3 4 5 6 7 R T (m s) Incongruent Congruent * * * * * * * * * Preceding trial number Incongruent Congruent Preceding trial number -100 0 100 200 300 400 500 Time (ms) Preceding trial(s) CM-1 CM-3 CM-7 CM-5 Incongruent Congruent Preceding trial(s) E E G B e h a v i o r a l cccccccC cccccccI cccccC cccC cC cI cccI cccccI c i C I 1 3 5 7 Number preceding (CM) Preceding Ending iiiiiiiC iiiiiiiI iiiiiC iiiC iC iI iiiI iiiiiI C I Ending Time P r e c e d i n g T r i a l ( s ) 1 - 7 E n d i n g t r i a l 1500 ms Wait for response 1500 ms Wait for response 1500 ms GREEN RED EEG data processing • EEG data were processed with a blind source separation algorithm, second-order blind identification (SOBI, [12,13]) to isolate frontal-midline EEG activity from other neuronal sources and artifact signals. Correct-related Negativity (CRN) • The CRN was quantified as the average voltage value (with respect to baseline) between the 0-100 ms interval following a button press response. 400 500 600 700 800 C ongruent Incongruent R T (m s) -2 -1.5 -1 -0.5 0 C ongruent Incongruent CRN am plitude (µV) Preceding trial(s) CM-1 CM-3 CM-7 CM-5 500 600 700 800 900 C ongruent Incongruent R T (m s) iiiiiI iiiiiC cccccI cccccC -2 -1.5 -1 -0.5 0 1 3 5 CRN am plitude (µV) 500 600 700 800 900 1 3 5 R T (m s) 400 500 600 700 800 1 3 5 7 R T (m s) cI cC iI iC Number of preceding trials Incongruent Congruent Incongruent Congruent Preceding trial(s) -100 0 100 200 300 400 500 Time (ms) - + 2 µV 0 100 iI iC cI cC Preceding trial(s) Incongruent Congruent cI cC iI iC Number of preceding trials cI cC iI iC Number of preceding trials 0 100 iiiI iiiC cccI cccC CM-1 vs 3,5,7: F(1,23) = 45.92, p < 0.001 CM-1 vs 3,5: F(1,23) = 36.19, p < 0.001 CM-1 vs 3,5: F(1,23) = 3.25, p = 0.085
description
INTRODUCTION. RESULTS. SUMMARY. cI. cI. cI. iI. iI. iI. iC. iC. iC. cC. cC. cC. -. +. iiiI. iiiiiI. iI. cccccI. cI. cccI. iiiC. iC. iiiiiC. cC. cccccC. cccC. 2 µV. 2 µV. 2 µV. -100. -100. -100. -100. 0. 0. 0. 0. 100. 100. 100. 100. 200. 200. 200. - PowerPoint PPT Presentation
Transcript of Stim
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3. Ending-trial assessment: RT and CRN weremodulated by the preceding context
Participants •Right-handed, healthy volunteers •Behavioral task: n=24 (12 males), mean age=24.6, range= 18-35 •EEG + behavioral task: n=24 (12 males), mean age=23.7, range=18-31
Task •Stroop color-identification task requiring button press responses.•2 x 2 x 4(3) repeated measures design with factors of preceding-trial
type (congruent vs. incongruent), ending-trial type (Congruent vs. Incongruent), and number of preceding trials (contextual manipulation, cm: 1, 3, 5, [7]). Each cell in the design is referred to as a “mini-block”.
• Example of a single “mini-block”:
EEG Data Collection •Continuous 128 channel data, sampling rate: 1000Hz, bandpass:1-100
Hz, nose reference, electrode locations recorded in 3D space.
634.22/CCC15
Department of Psychology1, Department of Neurosciences2, Department of Computer Science3, University of New Mexico, Albuquerque, NM
Limited Modulation of the Stroop Interference Effect by up to 3 Preceding Trials
M.T. Sutherland1 and A.C. Tang1,2,3
REFERENCESREFERENCES
ACKNOWLEDGEMENTSACKNOWLEDGEMENTS
1.CRN and ERN were present in the same frontal-midline component that captured ACC activity.
INTRODUCTIONINTRODUCTION Frontal-midline EEG activity in the form of negative deflections in event-related brain potentials (e.g., the error-related negativity, ERN), has been considered to reflect aspects of anterior cingulate cortex (ACC) activity related to performance monitoring [1-6]. Bartholow et al. [5] have shown that the correct-related negativity (CRN, [7]) is sensitive to strategic expectations about an upcoming trial. Using a design where the probability of incongruent (I) or congruent (C) trials was manipulated over large blocks (e.g., C-80%: I-20%), CRN amplitude increased when the less probable trial type was encountered for both I and C trials. CRN modulation for C trials is unexpected according to conflict monitoring [3] because C trials are unlikely to induce response-conflict regardless of context. Bartholow et al. suggested a broadening of the conflict monitoring hypothesis to include other forms of conflict in addition to that at the response level. In the present study a different contextual manipulation was employed to further assess CRN modulation. Previously, the compatibility level (I vs. C) of the preceding trial has been shown to affect reaction times (RTs) and ACC activity on a current trial []. However, the number of preceding trials has not been considered as an important source of variance for current-trial RT.
1. Ridderinkhof K.R., Ullsperger M., Crone E.A., Nieuwenhuiss S. (2004). The role of the medial frontal cortex in cognitive control. Science, 306:443-447.
2. Ullsperger M., von Cramon D.Y. (2004). Neuroimaging of performance monitoring: Error detection and beyond. Cortex, 40:593-604.
3. Botvinick M.M., Braver T.S., Barch D.M., Carter C.S., Cohen J.D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108:624-652.
4. Luu P., Flaisch T., Tucker D.M. (2000). Medial frontal cortex in action monitoring. J. Neurosci., 20:464-469.
5. Bartholow B.D., Pearson M.A., Dickter C.L., Sher K.J., Fabiani M., Gratton G. (2005). Strategic control and medial frontal negativity: beyond errors and response conflict. Psychophysiology. 42:33-42.
6. Taylor S.F., Stern E.R., Gehring W.J. (2007). Neural systems for error monitoring: recent findings and theoretical perspectives. Neuroscientist, 13:160-172.
7. Vidal F., Hasbroucq T., Grapperon J., Bonnet M. (2000). Is the 'error negativity' specific to errors? Biol Psychol, 51:109-128.
8. Botvinick M., Nystrom L.E., Fissell K., Carter C.S., Cohen J.D. (1999). Conflict monitoring versus selection-for-action in anterior cingulate cortex. Nature, 402:179-181.
9. Egner T., Hirsch J. (2005). The neural correlates and functional integration of cognitive control in a Stroop task. NeuroImage, 24:539-547.
10. Gratton G., Coles M.G., Donchin E. (1992) .Optimizing the use of information: strategic control of activation of responses. J Exp Psychol Gen, 121:480-506.
11. Kerns J.G., Cohen J.D., MacDonald A.W., 3rd, Cho R.Y., Stenger V.A., Carter C.S. (2004). Anterior cingulate conflict monitoring and adjustments in control. Science, 303:1023-1026.
12. Belouchrani A., Abed-Meraim K., Cardoso J-F, Moulines E. (1997). A blind source separation technique using second-order statistics. IEEE Trans on Signal Proc, 45:434-444.
13. Tang A.C., Sutherland M.T., McKinney C.J. (2005). Validation of SOBI components from high density EEG. NeuoImage, 25:539-553.
This work was funded by a grant to ACT from the Sandia National Labs (#75111). We thank Amy Korzekwa, Masato Nakazawa, and Zhen Yang for assistance during data collection.
1. The SOBI recovered frontal-midline components likely capture aspects of ACC function.
2. The CRN and ERN may share a similar neural generator since both of these ERP deflections were captured in a single component.
3. The reduction of the Stroop interference effect (I-C) following a preceding i trial, in comparison to following a c trial, was diminished in the current study when only one preceding trial was delivered before the ending-trial of interest (CM-1).
4. The CRN was modulated by the contextual manipulations in the present study. (we need to say what this means to existing theory)
2. Preceding-trial assessment: RT and CRNamplitude differed across preceding trial numbers
4. Modulation of RT was unlikely to be explained as a speed-accuracy tradeoff: Error rates
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identification (SOBI, [12,13]) to isolate frontal-midline EEG activity from other neuronal sources and artifact signals.
Correct-related Negativity (CRN) • The CRN was quantified as the average voltage value (with respect to baseline) between the 0-
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CM-1 vs 3,5,7: F(1,23) = 45.92, p < 0.001
CM-1 vs 3,5: F(1,23) = 36.19, p < 0.001
CM-1 vs 3,5: F(1,23) = 3.25, p = 0.085
